research-article

A learning approach for query planning on spatio-temporal IoT data

Authors:

Hoan Nguyen Mau Quoc,

Martin Serrano,

John G. Breslin,

Danh Le PhuocAuthors Info & Claims

IOT '18: Proceedings of the 8th International Conference on the Internet of Things

Article No.: 1, Pages 1 - 8

https://doi.org/10.1145/3277593.3277598

Published: 15 October 2018 Publication History

Abstract

The ever-increasing growth of the Internet of Things (IoT) has attracted a considerable amount of research attention from the Semantic Web community in order to address the challenge of poor interoperability. However, our survey of research work has shown that the goal of providing an intelligent processing and analysis engine for IoT has still not been fully achieved. Central to this problem is the requirement for a semantic spatio-temporal query processing engine that is able to not only analyze spatio-temporal correlations in a massive amount of IoT data, but that can also generate an effective query plan for a given query to execute in a timely manner. Needless to say, query planning for the multidimensional data like IoT is a costly operation. The most known techniques are either based on the cost model or by using spatio-temporal data statistics and heuristics. In this paper, we propose an alternative solution that uses query similarity identification in conjunction with machine learning techniques to recommend a previously generated query plan to the optimizer for a given query. Our approach also aims to predict the query execution time for the purposes of workload management and capacity planning. Our extensive experiments indicate the efficiency of our learning approach with an impressive prediction accuracy on test queries.

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Cited By

Ryandana FNuha HAriyanto E(2022)Query Optimization for Room Temperature Sensor using Principal Component Analysis2022 6th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)10.1109/ICITISEE57756.2022.10057776(677-681)Online publication date: 13-Dec-2022
https://doi.org/10.1109/ICITISEE57756.2022.10057776
Guo SXu J(2021)CPRQ: Cost Prediction for Range Queries in Moving Object DatabasesISPRS International Journal of Geo-Information10.3390/ijgi1007046810:7(468)Online publication date: 8-Jul-2021
https://doi.org/10.3390/ijgi10070468
Li YChen CDuan MZeng ZLi K(2021)Attention-Aware Encoder–Decoder Neural Networks for Heterogeneous Graphs of ThingsIEEE Transactions on Industrial Informatics10.1109/TII.2020.302559217:4(2890-2898)Online publication date: Apr-2021
https://doi.org/10.1109/TII.2020.3025592
Show More Cited By

A learning approach for query planning on spatio-temporal IoT data
1. Information systems
  1. Data management systems
    1. Database management system engines
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory

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Published In

cover image ACM Other conferences

IOT '18: Proceedings of the 8th International Conference on the Internet of Things

October 2018

299 pages

ISBN:9781450365642

DOI:10.1145/3277593

Conference Chairs:
Krzysztof Janowicz
University of California, Santa Barbara
,
Werner Kuhn
University of California, Santa Barbara
,
Program Chairs:
Federica Cena
University of Torino, Italy
,
Armin Haller
Australian National University, Australia
,
Kyriakos G. Vamvoudakis
Georgia Institute of Technology, Georgia Tech

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 October 2018

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Funding Sources

BIG-IoT project
SFI
Marie Skodowska-Curie Programme

Conference

IOT '18

IOT '18: 8th International Conference on the Internet of Things

October 15 - 18, 2018

California, Santa Barbara, USA

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Overall Acceptance Rate 28 of 84 submissions, 33%

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Cited By

Ryandana FNuha HAriyanto E(2022)Query Optimization for Room Temperature Sensor using Principal Component Analysis2022 6th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)10.1109/ICITISEE57756.2022.10057776(677-681)Online publication date: 13-Dec-2022
https://doi.org/10.1109/ICITISEE57756.2022.10057776
Guo SXu J(2021)CPRQ: Cost Prediction for Range Queries in Moving Object DatabasesISPRS International Journal of Geo-Information10.3390/ijgi1007046810:7(468)Online publication date: 8-Jul-2021
https://doi.org/10.3390/ijgi10070468
Li YChen CDuan MZeng ZLi K(2021)Attention-Aware Encoder–Decoder Neural Networks for Heterogeneous Graphs of ThingsIEEE Transactions on Industrial Informatics10.1109/TII.2020.302559217:4(2890-2898)Online publication date: Apr-2021
https://doi.org/10.1109/TII.2020.3025592
Chu WTsai H(2021)Rectilinear Range Query Processing on SpatialHadoop Platform2021 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOBECOM46510.2021.9685052(1-6)Online publication date: Dec-2021
https://doi.org/10.1109/GLOBECOM46510.2021.9685052
Gao WQian CHatcher WLiao WLu CYu W(2021)Towards Scalability of the IoT Search Engine2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00092(521-528)Online publication date: Oct-2021
https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00092
Nguyen Mau Quoc HSerrano MMau Nguyen HG. Breslin JLe-Phuoc D(2019)EAGLE—A Scalable Query Processing Engine for Linked Sensor DataSensors10.3390/s1920436219:20(4362)Online publication date: 9-Oct-2019
https://doi.org/10.3390/s19204362
Sagkriotis SKolomvatsos KAnagnostopoulos CPezaros DHadjiefthymiades S(2019)Knowledge-centric Analytics Queries Allocation in Edge Computing Environments2019 IEEE Symposium on Computers and Communications (ISCC)10.1109/ISCC47284.2019.8969706(1-6)Online publication date: Jun-2019
https://doi.org/10.1109/ISCC47284.2019.8969706
Liang FQian CHatcher WYu W(2019)Search Engine for the Internet of Things: Lessons From Web Search, Vision, and OpportunitiesIEEE Access10.1109/ACCESS.2019.29316597(104673-104691)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2931659

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